A heating system intelligent valve group control system and method

Abstract

The application discloses a kind of heating system intelligent valve group control system and method, it is related to intelligent valve control technical field, and the intelligent operation of heating system is realized by sensing, decision-making, three-tier architecture of execution, sensing layer uses multi-sensor fusion and double RS485 redundant communication network, and real-time acquisition pressure, flow, temperature data;Decision-making layer is based on leakage determination model and heat load algorithm to generate instruction;Execution layer realizes quick shutdown, intelligent drain and gradual water filling by valve linkage.The application solves the problems of slow response, high false alarm, high water hammer risk and unreliable communication in the prior art, the leakage response time is less than 3s, the false alarm rate is less than 0.3 times per 10,000 hours, the operation and maintenance labor cost is reduced by 60%, the valve life is extended by 2.4 times, and it is suitable for DN15-DN500 pipe diameter and supports smart heating platform docking, realizes the upgrade from passive repair to active protection, intelligent recovery.

Description

Technical Field

[0001] This invention relates to the field of intelligent valve control technology, and more specifically to an intelligent valve group control system and method for a heating system. Background Technology

[0002] Currently, intelligent valve groups are the core control units of heating systems, primarily responsible for functions such as remote shutdown and automatic water supply, which are crucial for ensuring heating safety and improving system efficiency. While existing technologies have achieved basic remote control, the following key issues remain: Delayed Leak Response: Existing systems have long response times to leaks, and delays in pressure signal transmission and valve action can easily escalate accidents, causing significant water waste and pipeline damage; High False Alarm Rate: Simple sensor data processing logic makes them susceptible to interference, leading to false alarms and frequent invalid shutdowns, affecting normal heating; High Water Supply Risk: Directly opening valves during water supply can easily generate water hammer, impacting pipes and equipment; incomplete venting leaves residual gas, reducing system efficiency; Poor Communication Reliability: Most systems use single-channel RS485 communication, which is prone to interruption under extreme conditions, resulting in the inability to transmit control commands and system malfunction; High Maintenance Costs: Short equipment lifespan and frequent replacement cycles; fault handling relies on manual troubleshooting, with an average processing time of approximately 4 hours, resulting in high labor costs; and a lack of preventative maintenance capabilities leads to significant losses from sudden shutdowns.

[0003] Therefore, there is an urgent need for an intelligent valve group control system that is fast-responding, has low false alarm rate, is shock resistant, has reliable communication, and low operation and maintenance cost, in order to meet the high reliability and low energy consumption requirements of smart heating systems. Summary of the Invention

[0004] In view of this, the present invention provides an intelligent valve group control system and method for a heating system to solve the problems existing in the background art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A smart valve group control system for a heating system includes a sensing layer, a decision-making layer, and an execution layer; The sensing layer includes a pressure sensor, an electromagnetic flow meter, a temperature sensor, and an RS485 communication network. The pressure sensor outputs a 4-20mA analog signal to monitor the pipeline pressure in real time. The electromagnetic flow meter collects supply and return water flow data and analyzes the heat load of the heat meter parameter analysis unit. The temperature sensor monitors the pipeline water temperature. The RS485 communication network adopts a master-slave architecture and supports the Modbus-RTU protocol. Each slave station aggregates data to the decision layer through a hub and receives control commands issued by the decision layer. The decision-making layer includes a host computer; the host computer has a built-in leakage judgment model and thermal load algorithm for generating control commands; The execution layer includes a water supply solenoid valve, a return water electric valve, a drain solenoid valve, and an electric actuator. The execution layer executes pipeline disconnection, water discharge, and automatic water supply actions according to the control instructions of the decision layer.

[0006] Optionally, the RS485 communication network of the sensing layer adopts a master-slave dual RS485 channel structure, with the two channels serving as backups for each other to ensure communication reliability under extreme operating conditions.

[0007] Optionally, the sampling frequency of the pressure sensor is ≥10Hz, and the flow data sampling accuracy of the electromagnetic flowmeter is ±1.5%FS. Optionally, the decision layer also includes a main control PLC. When the pressure sensor detects a sudden drop in pipeline pressure ΔP ≥ 0.1MPa / s, the main control PLC immediately triggers an alarm signal and controls the supply solenoid valve and return electric valve to close synchronously within ≤3s, while simultaneously opening the supply and return water drain solenoid valves. Optionally, the main control PLC continuously monitors the pipeline pressure. When the pressure drops to 0MPa, it automatically closes the supply and return water drain solenoid valves to stop water leakage. Optionally, when the execution layer performs the automatic water filling action, the main control PLC first controls the return electric valve to open slightly at 5%. After the pipeline pressure rises to a set threshold of 0.2MPa, the total water filling is monitored through the electromagnetic flowmeter. When the water filling reaches a preset value, the main control PLC controls the closure of the supply and return water drain solenoid valves and restores the supply solenoid valve to the fully open state. Optionally, the host computer also includes a big data fault prediction function, which predicts faults based on historical and real-time data collected by the perception layer. Optionally, the host computer also includes an open interface for seamless integration with a smart heating platform. A method for controlling an intelligent valve group in a heating system includes: S1. Data Acquisition: Pressure sensors, electromagnetic flow meters, and temperature sensors in the sensing layer collect real-time data on pipeline pressure, flow rate, and water temperature, and transmit the data to the host computer via a dual RS485 communication network. S2. Fault Judgment and Response: The host computer analyzes the pressure data through the leakage judgment model. If a sudden pressure drop ΔP ≥ 0.1MPa / s is detected, a leakage control command is generated. After receiving the command, the main control PLC controls the water supply solenoid valve and the return water electric valve to close within ≤3s, and at the same time opens the water supply and return water drain solenoid valves. When the pressure drops to 0MPa, the drain solenoid valve is closed. S3. Automatic water supply recovery: After maintenance, the water supply process is started by manual reset or command from the host computer; the main control PLC controls the return water electric valve to open slightly by 5%, and after the pressure rises to 0.2MPa, the total water supply is monitored by the flow meter; after the standard is met, the drain solenoid valve is closed and the water supply solenoid valve is fully opened to complete the water supply. S4. Operation and Maintenance Monitoring: The host computer analyzes flow and heat meter data through heat load algorithm, and combines big data fault prediction function to realize preventive maintenance and system status monitoring.

[0008] As can be seen from the above technical solution, compared with the prior art, the present invention discloses an intelligent valve group control system and method for a heating system, which has the following significant beneficial effects: Safety performance is greatly improved: the leakage response time is less than 3 seconds, which is 5 times better than the industry standard, and the scope of the accident can be controlled quickly; the false alarm rate is less than 0.3 times / 10,000 hours, reducing the impact of ineffective shutdowns on heating.

[0009] High operational reliability: Dual RS485 redundant communication channels ensure uninterrupted communication even under extreme conditions; gradual water filling completely eliminates water hammer effect and ensures clean exhaust, improving system operating efficiency.

[0010] Operation and maintenance costs are significantly reduced: not only are labor costs reduced, but also equipment procurement and replacement costs are decreased; Highly scalable: Adaptable to pipe diameters from DN15 to DN500, meeting the needs of heating networks of different scales; The host computer provides a standardized API interface, which can be seamlessly connected to the smart heating platform and supports digital twin modeling, in line with the development trend of smart heating. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the system structure provided by the present invention; Figure 2 This is a schematic diagram illustrating the operation of the valve assembly provided by the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] This invention discloses an intelligent valve group control system for a heating system, such as... Figure 1 and Figure 2 As shown, it includes a perception layer, a decision-making layer, and an execution layer; The sensing layer includes pressure sensors, electromagnetic flow meters, temperature sensors, and an RS485 communication network. The pressure sensors output 4-20mA analog signals to monitor pipeline pressure in real time. The electromagnetic flow meters collect supply and return water flow data and analyze the unit's heat load by combining this data with heat meter parameters (such as calorific value). The temperature sensors monitor pipeline water temperature to help determine the system's operating status. The RS485 communication network adopts a master-slave architecture and supports the Modbus-RTU protocol to ensure efficient transmission of motor parameters (valve opening) and heat meter data. Each slave station (valve, sensor) aggregates data to the decision-making layer via a hub and receives control commands from the decision-making layer. The decision-making layer includes a host computer; the host computer has a built-in leakage detection model and thermal load algorithm for generating control commands; The execution layer includes water supply solenoid valves, return water electric valves, drain water solenoid valves, and electric actuators. The execution layer executes pipeline disconnection, water discharge, and automatic water supply actions according to the control instructions of the decision layer.

[0015] In one specific embodiment, the RS485 communication network of the sensing layer adopts a master-slave dual RS485 channel structure, with the two channels serving as backups for each other to ensure communication reliability under extreme operating conditions.

[0016] In one specific embodiment, the pressure sensor's sampling frequency is ≥10Hz, and the electromagnetic flow meter's flow data sampling accuracy is ±1.5%FS. In another specific embodiment, when the pressure sensor detects a sudden drop in pipeline pressure ΔP ≥ 0.1MPa / s, the main control PLC immediately triggers an alarm signal and controls the supply water solenoid valve and return water electric valve to close synchronously within ≤3s, while simultaneously opening the supply and return water drain solenoid valves to accelerate drainage. The main control PLC continuously monitors the pipeline pressure, and when the pressure drops to 0MPa, it automatically closes the supply and return water drain solenoid valves to stop drainage. A graded response strategy is adopted: the valve action priority is dynamically adjusted according to the leakage rate.

[0017] In one specific embodiment, when the execution layer performs the automatic water supply action, the main control PLC first controls the return water electric valve to open slightly at 5%. After the pipeline pressure rises to the set threshold of 0.2MPa, the total water supply is monitored by an electromagnetic flow meter. When the water supply reaches the preset value, the main control PLC controls the closing of the supply and return water drain solenoid valves and restores the supply solenoid valve to the fully open state. By adopting a gradual valve opening, the water hammer effect is avoided.

[0018] By adopting the above control system, the following effects can be achieved: Safety performance: Leakage response time <3s, 5 times better than the industry standard (15s). False alarm rate <0.3 times / 10,000 hours, reducing unnecessary downtime.

[0019] Operation and maintenance costs: Operation and maintenance costs are significantly reduced; Maintenance efficiency: The average troubleshooting time has been reduced from 4 hours to 1 hour, and labor costs have been reduced by 60%.

[0020] Equipment lifespan: Valve operating life > 120,000 cycles (national standard 50,000 cycles), extending the replacement cycle by 2.4 times.

[0021] Preventative maintenance: Big data predicts faults with an accuracy rate of 85%, reducing losses from sudden downtime.

[0022] Scalability: Supports pipe diameters from DN15 to DN500 and is compatible with the API interface of the smart heating platform.

[0023] Open API: Provides standardized APIs for seamless integration with smart heating platforms.

[0024] Modular design: allows for rapid expansion of sensor nodes or control units, adapting to the transformation of old systems.

[0025] A method for controlling an intelligent valve group in a heating system, comprising: S1. Data Acquisition: Pressure sensors, electromagnetic flow meters, and temperature sensors in the sensing layer collect real-time data on pipeline pressure, flow rate, and water temperature, and transmit the data to the host computer via a dual RS485 communication network. S2. Fault Judgment and Response: The host computer analyzes the pressure data through the leakage judgment model. If a sudden pressure drop ΔP ≥ 0.1MPa / s is detected, a leakage control command is generated. After receiving the command, the main control PLC controls the water supply solenoid valve and the return water electric valve to close within ≤3s, and at the same time opens the water supply and return water drain solenoid valves. When the pressure drops to 0MPa, the drain solenoid valve is closed. S3. Automatic water supply recovery: After maintenance, the water supply process is started by manual reset or command from the host computer; the main control PLC controls the return water electric valve to open slightly by 5%, and after the pressure rises to 0.2MPa, the total water supply is monitored by the flow meter; after the standard is met, the drain solenoid valve is closed and the water supply solenoid valve is fully opened to complete the water supply. S4. Operation and Maintenance Monitoring: The host computer analyzes flow and heat meter data through heat load algorithm, and combines big data fault prediction function to realize preventive maintenance and system status monitoring.

[0026] The control method of this invention integrates pressure protection, heat load regulation, and intelligent drainage into a unified control logic. It not only completely solves the problem of incomplete venting in traditional systems through a three-stage water supply process of micro-opening-detection-full opening, but also achieves a leap from passive emergency repairs to active protection and intelligent recovery, providing a standardized and highly reliable terminal control node for smart heating systems.

[0027] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0028] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A smart valve group control system for a heating system, characterized in that, It includes the perception layer, decision-making layer, and execution layer; The sensing layer includes a pressure sensor, an electromagnetic flow meter, a temperature sensor, and an RS485 communication network. The pressure sensor outputs a 4-20mA analog signal to monitor the pipeline pressure in real time. The electromagnetic flow meter collects supply and return water flow data and analyzes the heat load of the heat meter parameter analysis unit. The temperature sensor monitors the pipeline water temperature. The RS485 communication network adopts a master-slave architecture and supports the Modbus-RTU protocol. Each slave station aggregates data to the decision layer through a hub and receives control commands issued by the decision layer. The decision-making layer includes a host computer; the host computer has a built-in leakage judgment model and thermal load algorithm for generating control commands; The execution layer includes a water supply solenoid valve, a return water electric valve, a drain solenoid valve, and an electric actuator. The execution layer executes pipeline disconnection, water discharge, and automatic water supply actions according to the control instructions of the decision layer.

2. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The RS485 communication network of the sensing layer adopts a master-slave dual RS485 channel structure, with the two channels serving as backups for each other to ensure communication reliability under extreme operating conditions.

3. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The pressure sensor has a sampling frequency of ≥10Hz, and the electromagnetic flow meter has a flow data sampling accuracy of ±1.5%FS.

4. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The decision-making layer also includes a main control PLC. When the pressure sensor detects a sudden drop in pipeline pressure ΔP ≥ 0.1 MPa / s, the main control PLC immediately triggers an alarm signal and controls the water supply solenoid valve and the return water electric valve to close synchronously within ≤ 3 seconds, while simultaneously opening the water supply and return water drain solenoid valves.

5. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The main control PLC continuously monitors the pipeline pressure. When the pressure drops to 0MPa, it automatically closes the supply and return water drain solenoid valve to stop the water drain.

6. The intelligent valve group control system for a heating system according to claim 4, characterized in that, When the execution layer performs the automatic water supply action, the main control PLC first controls the return water electric valve to open slightly at 5%. After the pipeline pressure rises to the set threshold of 0.2MPa, the total water supply is monitored by the electromagnetic flow meter. When the water supply reaches the preset value, the main control PLC controls the closing of the supply and return water drain solenoid valves and restores the supply solenoid valve to the fully open state.

7. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The host computer also includes a big data fault prediction function, which performs fault prediction based on historical and real-time data collected by the perception layer.

8. The intelligent valve group control system for a heating system according to claim 1, characterized in that, The host computer also includes an open interface for seamless integration with the smart heating platform.

9. A method for controlling an intelligent valve group in a heating system, characterized in that, The intelligent valve group control system for a heating system according to any one of claims 1-8 includes: S1. Data Acquisition: Pressure sensors, electromagnetic flow meters, and temperature sensors in the sensing layer collect real-time data on pipeline pressure, flow rate, and water temperature, and transmit the data to the host computer via a dual RS485 communication network. S2. Fault Judgment and Response: The host computer analyzes the pressure data through the leakage judgment model. If a sudden pressure drop ΔP ≥ 0.1MPa / s is detected, a leakage control command is generated. After receiving the command, the main control PLC controls the water supply solenoid valve and the return water electric valve to close within ≤3s, and at the same time opens the water supply and return water drain solenoid valves. When the pressure drops to 0MPa, the drain solenoid valve is closed. S3. Automatic water supply recovery: After maintenance, the water supply process is started by manual reset or command from the host computer; the main control PLC controls the return water electric valve to open slightly by 5%, and after the pressure rises to 0.2MPa, the total water supply is monitored by the flow meter; after the standard is met, the drain solenoid valve is closed and the water supply solenoid valve is fully opened to complete the water supply. S4. Operation and Maintenance Monitoring: The host computer analyzes flow and heat meter data through heat load algorithm, and combines big data fault prediction function to realize preventive maintenance and system status monitoring.

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